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We preserve the same names for various types of time consistency for both the random variables and the stochastic processes.
In this case, both x j and Y j are random variables, but for notational simplicity in this work l k, Y j and x j denote both the random variables and the values they may assume.
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We also note, for clarity's sake, in the following analyses we abuse notation and use x jk for both the random variable and its realization.
(For ease of notational simplicity, in (8) we use the same symbol to denote both the random variable (in the second term) and its realization (in the third and fourth terms).
If the r.v.s {X i : i ≥ 1} are both WUOD and WLOD, we call the random variables are widely orthant dependent(WOD).
Probabilistic sensitivity measures have been developed for both the original and additional random variables such that the significance of the random variables can be determined.
The random variables are conditionally independent given.
The random variables are iid and.
The random variables are classified into two classes, namely discrete and continuous random variables.
Assume that the random variables are stochastically dominated by a random variable.
These are just the random variables inevitably stemming from mass pharmaceuticals.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com